文献类型： 外文期刊
作者： He, Lei 1 ; Wang, Jian 2 ; Peltier, Drew M. P. 4 ; Ritter, Francois 5 ; Ciais, Philippe 5 ; Penuelas, Josep 6 ; Xiao, Jingfeng 8 ; Crowther, Thomas W. 9 ; Li, Xing 10 ; Ye, Jian-Sheng 11 ; Sasaki, Takehiro 12 ; Zhou, Chenghu 13 ; Li, Zhao-Liang 1 ;
作者机构： 1.Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, State Key Lab Efficient Utilizat Arable Land China, Beijing, Peoples R China
2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing, Peoples R China
3.Univ Chinese Acad Sci, Beijing, Peoples R China
4.Univ Nevada Las Vegas, Sch Life Sci, Las Vegas, NV USA
5.Univ Paris Saclay, Lab Sci Climat & Environm, CEA, CNRS,UVSQ, Gif Sur Yvette, France
6.Global Ecol CREAF CSIC UAB, CSIC, Cerdanyola Del Valles, Barcelona, Spain
7.CREAF, Cerdanyola Del Valles, Barcelona, Spain
8.Univ New Hampshire, Earth Syst Res Ctr, Inst Study Earth Oceans & Space, Durham, NH USA
9.Swiss Fed Inst Technol, Inst Integrat Biol, Swiss Fed Inst Technol, Zurich, Switzerland
10.Sun Yat Sen Univ, Sch Geog & Planning, Guangzhou, Peoples R China
11.Lanzhou Univ, Coll Ecol, State Key Lab Herbage Improvement & Grassland Agro, Lanzhou, Peoples R China
12.Yokohama Natl Univ, Grad Sch Environm & Informat Sci, Yokohama, Japan
13.Guangdong Acad Sci, Guangzhou Inst Geog, Ctr Ocean Remote Sensing, Southern Marine Sci & Engn Guangdong Lab Guangzhou, Guangzhou, Peoples R China
14.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China
期刊名称：NATURE ECOLOGY & EVOLUTION （ 影响因子：14.5； 五年影响因子：17.6 ）
ISSN： 2397-334X
年卷期： 2025 年
页码：
收录情况： SCI
摘要： Precipitation effects on plant carbon uptake extend beyond immediate timeframes, reflecting temporal lags between rainfall and plant growth. Mechanisms and relative importance of such lagged effects are expected to vary across ecosystems. Here we draw on an extensive collections of productivity proxies from long-term ground measurements, satellite observations and model simulations to show that preceding-year precipitation exerts a comparable influence on plant productivity to current-year precipitation. Statistically supported lagged precipitation effects are detected in 13.4%-19.7% of the grids depending on the data source. In these sites, preceding-year precipitation positively controls current-year plant productivity in water-limited areas, while negative effects occur in some wet regions, such as tropical forests. While aridity emerges as the main driver of this spatial variability, machine learning-based spatial attribution also indicates interactions among plant traits, climatic conditions and soil properties. We also show that soil water dynamics, plant phenology and foliar structure might mediate lagged precipitation effects across time. Our findings highlight the role of preceding-year precipitation in global plant productivity.
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